Abstract 5647: Single cell, multiomic spatial phenotyping of immunotherapy responses in head and neck cancer

Background: Immune checkpoint inhibitors (ICI) have proven to be game-changing treatments for mucosal head and neck squamous cell cancer (HNSCC). Emerging successes with anti-PD-1/PD-L1 therapy have led to durable responses and prolonged survival in both human papillomavirus-positive (HPV+) and negative (HPV-) patients. There is now a need for predictive biomarkers to guide patient selection for highly targeted ICI therapies as currently available diagnostic biomarkers have a limited value. The tumor microenvironment (TME) composition, contexture, and cellular architecture are now recognized as key to understanding immune responsive and resistant phenotypes. Here, we are using a spatial biology approach to explore the TME in metastatic/recurrent HNSCC tumors treated with Pembrolizumab/Nivolumab.

Methods: In this study, we used single cell, multiomic spatial phenotyping utilizing the PhenoCycler-Fusion spatial biology platform to characterize the TME of HNSCC tumors from a cohort of n=40 patients. The discovery cohort consisted of patients who had complete vs. partial vs. stable vs. progressive responses to ICI therapy. We first analyzed tissues using an ultrahigh-plex antibody panel of >60 antibodies that label immune cell lineages, checkpoints, activation markers as well as tissue structure and the stroma. We then conducted whole-slide, single cell resolution RNA detection with complementary markers on serial sections from the same tissue blocks; the combination of these data allowed us to obtain multiomic spatial signatures that offered uniquely comprehensive insight into the TME of our tissue cohorts.

Results: Our study identified highly resolved tissue immune contexture analysis and metabolic tissue signatures associated with resistance and sensitivity to immunotherapy. Most notably, multiomic profiling of HNSCC tumours provided deeper insights into ICI therapy resistance than the single omics based approaches alone.

Conclusions: Our study demonstrates the power of unbiased, multiomic spatial phenotyping with whole-slide imaging to identify biomarkers associated with response to ICI therapy in HNSCC.

Citation Format: HaYeun Ji, Niyati Jhaveri, Ning Ma, Bassem B. Cheikh, Aditya Pratapa, James Monkman, Ken O’Byrne, Brett Hughes, Arutha Kulasinghe, Oliver Braubach. Single cell, multiomic spatial phenotyping of immunotherapy responses in head and neck cancer. [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 5647.

Abstract 5626: Multiomic spatial profiling of the tumor immune microenvironment at single cell resolution

Background: It has been well established that the tumor microenvironment (TME), which comprises cancer cells, stromal cells, and surrounding extracellular matrix, plays a critical role in cancer development, progression, and control. The immunological components within tumors, known as the tumor immune microenvironment (TiME), have also been implicated in tumor development, recurrence, and metastasis. Effective strategies for cancer immunotherapies will require a deep understanding of the factors that shape both the TME and TiME. Here, we describe a spatial multiomics approach that utilizes RNAscope™ ISH technology paired with high-plex whole-slide spatial phenotyping with the PhenoCycler™-Fusion platform. This two-step approach is compatible with human FFPE tissues and enables researchers to characterize the spatial biology of the TiME more accurately by detecting RNA and protein markers on serial sections. The resulting multiomic data more accurately reveal the interplay between TME and TiME by giving insight into cell lineages, surrounding structures, as well as secreted chemokines and cytokines that exist within the TME ecosystem.

Methods: We performed ultrahigh-plex spatial phenotyping on the PhenoCycler-Fusion on FFPE tumor tissue sections, using an antibody panel that is designed for immune cell phenotyping, evaluation of immune contexture and proliferation across the TME. Using serial sections from the same tissue blocks, we then ran the RNAscope HiPlex v2 assay automated on the PhenoCycler-Fusion system. This assay consisted of a 12-plex immuno-oncology panel of RNA target probes, which were selected to detect macrophages, chemokines, and cytokines within tumors. We used Phenoplex software to analyze the protein and RNA datasets and to compute cell phenotypes and spatial associations.

Results and Conclusions: In this proof-of-concept study, we demonstrate the utility of multiomic spatial profiling on the PhenoCycler-Fusion platform. Analysis of the resulting multiplex imaging data not only revealed the structural organization of cells within the TME, but also activation states of immune cells. Together, this information provides a more complete functional map of immune cells within the TME and TiME and thereby enriches our understanding of tumor biology that may be deterministic of immunotherapy responsiveness. This work paves the way for future research that will rely on deep spatial phenotyping with protein biomarkers coupled with accurate quantification of the expression of regulatory cytokines, chemokines, growth factors, or non-coding RNAs that only RNA probes can detect.

Citation Format: Niyati Jhaveri, HaYeun Ji, Anushka Dikshit, Jessica Yuan, Emerald Doolittle, Steve Zhou, Maithreyan Srinivasan, Bassem B. Cheikh, Fabian Schneider, James Mansfield, Julia Kennedy-Darling, Oliver Braubach. Multiomic spatial profiling of the tumor immune microenvironment at single cell resolution. [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 5626.

Abstract 2531: a

Hepatocellular carcinoma (HCC) is an emerging health crisis due to rapidly increasing incidence rates and an overall 5-year survival rate of 18%. Consequently, there is an urgent need for new therapies and better preventive strategies. Aging and obesity are two of the biggest risk factors for HCC, and with ever-increasing aging and obese populations, uncovering how aging and obesity drive the increased risk for HCC has become imperative. Aging and obesity are well known to be characterized by immune dysregulation leading to persistent inflammation, and a dysregulated immune microenvironment is also a common theme shared by multiple hallmarks of HCC. In this study, we aim to assess the immune microenvironment of aged and obese mouse livers by performing spatial phenotyping of distinct immune signatures which can potentially predispose hepatocytes to HCC. To address this, we used Akoya’s ultra-high multiplexed CODEX (CO-Detection by indEXing) imaging system to interrogate 31 different biomarkers in liver samples at the single cell level. Specifically, we compared the liver immune microenvironment of mice within 2 different treatment groups (old mice on a high fat diet (HFD) and young mice on a normal diet (ND)) to the immune landscape of liver tumor tissue. Our goal is to identify distinct immune phenotypes present in both, liver tumor tissues and livers of HFD mice, compared to ND livers - to better understand how immune dysregulation can predispose an aged and obese liver to HCC.

Citation Format: Adarsh Rajesh, Aaron Havas, Siva Karthik Varanasi, Katrina Evans, Bassem B. Cheikh, Clemens Duerrschmid, Najiba Mammadova, Peter Adams, Susan Kaech. a [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 2531.